{"id":"https://openalex.org/W2565321812","doi":"https://doi.org/10.1109/icip.2017.8296572","title":"Compressive image recovery using recurrent generative model","display_name":"Compressive image recovery using recurrent generative model","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2565321812","doi":"https://doi.org/10.1109/icip.2017.8296572","mag":"2565321812"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1612.04229","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058219160","display_name":"Akshat Dave","orcid":"https://orcid.org/0000-0003-0560-632X"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Akshat Dave","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011595399","display_name":"Anil Kumar Vadathya","orcid":"https://orcid.org/0000-0002-0517-0901"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anil Kumar Vadathya","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, IN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, IN","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006862080","display_name":"Kaushik Mitra","orcid":"https://orcid.org/0000-0001-6747-9050"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kaushik Mitra","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, IN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, IN","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":null,"first_page":"1702","last_page":"1706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7564408779144287},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6970398426055908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6244382262229919},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.616413950920105},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5684801340103149},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5648733377456665},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5398864150047302},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5314867496490479},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5308542847633362},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4894620180130005},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41754886507987976},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3697759211063385},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3501865565776825}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7564408779144287},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6970398426055908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6244382262229919},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.616413950920105},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5684801340103149},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5648733377456665},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5398864150047302},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5314867496490479},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5308542847633362},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4894620180130005},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41754886507987976},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3697759211063385},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3501865565776825},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icip.2017.8296572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1612.04229","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1612.04229","pdf_url":"https://arxiv.org/pdf/1612.04229","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2565321812","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1612.04229.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1612.04229","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1612.04229","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1612.04229","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1612.04229","pdf_url":"https://arxiv.org/pdf/1612.04229","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2565321812.pdf","grobid_xml":"https://content.openalex.org/works/W2565321812.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1485262465","https://openalex.org/W1522301498","https://openalex.org/W1758098838","https://openalex.org/W1969260924","https://openalex.org/W2036648611","https://openalex.org/W2037642501","https://openalex.org/W2056758595","https://openalex.org/W2082029531","https://openalex.org/W2095451930","https://openalex.org/W2099471712","https://openalex.org/W2122548617","https://openalex.org/W2130120519","https://openalex.org/W2145096794","https://openalex.org/W2160547390","https://openalex.org/W2219727625","https://openalex.org/W2273561594","https://openalex.org/W2296616510","https://openalex.org/W2951004968","https://openalex.org/W2951638509","https://openalex.org/W2952101880","https://openalex.org/W4249179470","https://openalex.org/W4250955649","https://openalex.org/W6639613013","https://openalex.org/W6642427631","https://openalex.org/W6674500526"],"related_works":["https://openalex.org/W2963634756","https://openalex.org/W2963501224","https://openalex.org/W2889828889","https://openalex.org/W2950577421","https://openalex.org/W1608074891","https://openalex.org/W3152186334","https://openalex.org/W2273561594","https://openalex.org/W1987090397","https://openalex.org/W2903562308","https://openalex.org/W2946879392","https://openalex.org/W2753116572","https://openalex.org/W2951189605","https://openalex.org/W3115447952","https://openalex.org/W2052403014","https://openalex.org/W2973045745","https://openalex.org/W2136682629","https://openalex.org/W2930857665","https://openalex.org/W2400818632","https://openalex.org/W2940632541","https://openalex.org/W3151138472"],"abstract_inverted_index":{"Reconstruction":[0],"of":[1],"signals":[2],"from":[3],"compressively":[4],"sensed":[5],"measurements":[6],"is":[7],"an":[8,22,63],"ill-posed":[9],"problem.":[10],"In":[11],"this":[12],"paper,":[13],"we":[14],"leverage":[15],"the":[16,55],"recurrent":[17],"generative":[18],"model,":[19],"RIDE,":[20],"as":[21],"image":[23,27],"prior":[24],"for":[25,68],"compressive":[26,44],"reconstruction.":[28],"Recurrent":[29],"networks":[30],"can":[31,39],"model":[32],"long-range":[33],"dependencies":[34],"in":[35,43,71],"images":[36,72],"and":[37,57,87,92],"hence":[38],"handle":[40],"global":[41,82],"multiplexing":[42],"imaging.":[45],"We":[46,61],"perform":[47],"MAP":[48],"inference":[49],"with":[50],"RIDE":[51],"using":[52],"back-propagation":[53],"to":[54,80],"inputs":[56],"projected":[58],"gradient":[59],"method.":[60],"propose":[62],"entropy":[64],"thresholding":[65],"based":[66],"approach":[67,75],"preserving":[69],"texture":[70],"well.":[73],"Our":[74],"shows":[76],"superior":[77],"reconstructions":[78],"compared":[79],"recent":[81],"reconstruction":[83],"approaches":[84],"like":[85],"D-AMP":[86],"TVAL3":[88],"on":[89],"both":[90],"simulated":[91],"real":[93],"data.":[94]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}